分享经济环境下租赁车辆随机供应的路径优化问题研究

The high volatility of customer demand and high fixed cost of transport capacity resource are impeding the development of logistics enterprises, and the logistics service platform under sharing economy environment provides a good opportunity for these logistics enterprises to solve the dilemma through renting external resources. Nevertheless, the changeable number of vehicles on logistics service platform gives rise to the stochastic supply of renting vehicles. Thus, taking the stochastic supply of renting vehicles as the starting point, this project intends to research on the vehicle routing problem in logistics transportation and distribution. The main research work consists of three parts. First, to analyze the substantive characteristics-the stochastic supply of renting vehicles-and dissect their impacts on vehicle routing problem, the vehicle routing optimization model with pure stochastic supply will be build, based on four different combination conditions that consider whether the customer demand has requirements as well as time windows. Second, to dissect the combined effects of the stochastic supply of renting vehicles and the stochastic demand of customer on vehicle routing problem, the vehicle routing optimization model with the coexistence of the two uncertainties will be build, based on different combination conditions and optimization criteria. Third, an efficient optimization algorithm will be designed, which associates large neighborhood search heuristic; in this process, isometric partitioning will be adopted to achieve the quick classification of consumers, and the consumer’s temporal-spatial information will be applied to guide the path planning. This project can extend the research category of vehicle routing problem, and then help to the joint development of logistics industry and sharing economy.

客户需求的高波动性和运力资源的高固定成本正困扰着物流企业的发展，而分享经济环境下的物流服务平台为物流企业利用外部资源解决面临的困境提供了良好的机遇，但平台车辆供给量不可控的波动性会导致租赁车辆具有随机供应特征。本项目拟以租赁车辆随机供应为切入点，研究物流运输与配送中的车辆路径问题，主要包括：分析租赁车辆随机供应的本质特征及其对车辆路径问题的影响，基于客户需求有无满足率要求、客户有无时间窗约束等不同组合条件，构建单纯租赁车辆随机供应情形的车辆路径优化模型；剖析租赁车辆随机供应和客户随机需求共存对车辆路径问题的影响，基于不同组合条件与优化准则，构建租赁车辆随机供应和客户随机需求共存情形的车辆路径优化模型；利用等角划分思想实现客户的快速分组，利用客户的时空信息指导路径规划，再融合大规模邻域搜索算法设计高效的优化算法。本项目的研究可以拓展车辆路径问题的研究范畴，也有助于物流业和分享经济的共同发展。

本项目研究分享经济环境下的车辆路径优化问题及其优化算法。由于基于分享经济的车辆租赁平台近年来未能在物流配送领域得到良好的发展，相应的研究问题进行了适当调整，目前主要完成了三个方面的问题：1）基于算法策略组成部分及相关参数对全局探索能力和局部开发能力的影响分析，构建了几类新型的改进算法，提高了算法的性能表现；2）基于算法在优化过程中状态的识别与调整，构建了几类算法的改进框架，嵌套方便且可以有效提升现有差分进化算法的性能；3）基于消费者满意度和配送人员工作公平性的考量，设计了几类车辆路径优化模型。实验结果表明，所设计算法改进方案有效的提高了算法性能，所构建的车辆路径优化模型可以提高消费者和配送人员的满意度。项目目前发表学术论文11篇，其中SCI检索论文7篇；此外，还有在审论文3篇和工作论文3篇。培养硕士生4名，项目组4名成员职称晋升。